1. Field of the Invention
The present embodiments relate to methods for personalizing news, and more particularly, methods, systems, and computer programs for prioritizing items, which may be of different types of media, in the new stream.
2. Description of the Related Art
The Internet has witnessed an explosive growth of online news. According to a recent report, more than 123 million people visited news websites such as Yahoo!™ News in May 2010, representing 57 percent of the total U.S. internet audience, with each visitor reading 43 pages on average. These numbers have been steadily increasing over the past years and show the growing appeal of reading news online.
Different people like different types of news content. In order to provide a better news-reading experience, some news websites recommend different types of media to users based on past behavior. Personalized news deliver a news stream to a user, according to the desires and use trends of the user. However, customizing the news stream is a complex problem because the number of news sources and the multiple types of available media continue to grow rapidly.
The different types of media may include news articles, videos, slideshows, tweets, photos, blogs, etc. However, creating a custom news stream for a user is challenging when different types of media are included. It is difficult to prioritize items from one type of media when compared to other types of media items because their use is different. Further, some items may carry little contextual information, such as a photograph, which complicates the determination of the content of the photograph.
Recommending interesting news articles to users has become extremely important for internet news providers looking to maintain users' interest. While existing Web services, such as Yahoo!, attract users' initial clicks, ways to engage users after their initial visit are largely under explored.
It is in this context that embodiments arise.